---
title: MCP Toolbox
sidebarTitle: MCP Toolbox
description: Learn how to use MCPToolbox with Agno to connect to MCP Toolbox for Databases with tool filtering capabilities.
---

**MCPToolbox** enables Agents to connect to Google's [MCP Toolbox for Databases](https://googleapis.github.io/genai-toolbox/getting-started/introduction/) with advanced filtering capabilities. It extends Agno's `MCPTools` functionality to filter tools by toolset or tool name, allowing agents to load only the specific database tools they need.

## Prerequisites

You'll need the following to use MCPToolbox:

```bash
pip install toolbox-core
```

Our default setup will also require you to have Docker or Podman installed, to run the MCP Toolbox server and database for the examples.

## Quick Start

Get started with MCPToolbox instantly using our fully functional demo.

```bash
# Clone the repo and navigate to the demo folder
git clone https://github.com/agno-agi/agno.git
cd agno/cookbook/tools/mcp/mcp_toolbox_demo

# Start the database and MCP Toolbox servers

# With Docker and Docker Compose
docker-compose up -d

# With Podman
podman compose up -d

# Install dependencies
uv sync

# Set your API key and run the basic agent
export OPENAI_API_KEY="your_openai_api_key"
uv run agent.py
```

This starts a PostgreSQL database with sample hotel data and an MCP Toolbox server that exposes database operations as filtered tools.

## Verification

To verify that your docker/podman setup is working correctly, you can check the database connection:

```bash
# Using Docker Compose
docker-compose exec db psql -U toolbox_user -d toolbox_db -c "SELECT COUNT(*) FROM hotels;"

# Using Podman
podman exec db psql -U toolbox_user -d toolbox_db -c "SELECT COUNT(*) FROM hotels;"
```

## Basic Example

Here's the simplest way to use MCPToolbox (after running the Quick Start setup):

```python
import asyncio
from agno.agent import Agent
from agno.models.openai import OpenAIChat
from agno.tools.mcp_toolbox import MCPToolbox

async def main():
    # Connect to the running MCP Toolbox server and filter to hotel tools only
    async with MCPToolbox(
        url="http://127.0.0.1:5001",
        toolsets=["hotel-management"]  # Only load hotel search tools
    ) as toolbox:
        agent = Agent(
            model=OpenAIChat(),
            tools=[toolbox],
            instructions="You help users find hotels. Always mention hotel ID, name, location, and price tier."
        )
        
        # Ask the agent to find hotels
        await agent.aprint_response("Find luxury hotels in Zurich")

# Run the example
asyncio.run(main())
```

## How MCPToolbox Works

MCPToolbox solves the **tool overload problem**. Without filtering, your agent gets overwhelmed with too many database tools:

**Without MCPToolbox (50+ tools):**
```python
# Agent gets ALL database tools - overwhelming!
tools = MCPTools(url="http://127.0.0.1:5001")  # 50+ tools
```

**With MCPToolbox (3 relevant tools):**  
```python
# Agent gets only hotel management tools - focused!
tools = MCPToolbox(url="http://127.0.0.1:5001", toolsets=["hotel-management"])  # 3 tools
```

**The flow:**
1. MCP Toolbox Server exposes 50+ database tools
2. MCPToolbox connects and loads ALL tools internally  
3. Filters to only the `hotel-management` toolset (3 tools)
4. Agent sees only the 3 relevant tools and stays focused

## Advanced Usage

### Multiple Toolsets

Load tools from multiple related toolsets:

```python cookbook/tools/mcp/mcp_toolbox_for_db.py
import asyncio
from textwrap import dedent
from agno.agent import Agent
from agno.tools.mcp_toolbox import MCPToolbox

url = "http://127.0.0.1:5001"

async def run_agent(message: str = None) -> None:
    """Run an interactive CLI for the Hotel agent with the given message."""

    async with MCPToolbox(
        url=url, toolsets=["hotel-management", "booking-system"]
    ) as db_tools:
        print(db_tools.functions)  # Print available tools for debugging
        agent = Agent(
            tools=[db_tools],
            instructions=dedent(
                """ \
                You're a helpful hotel assistant. You handle hotel searching, booking and
                cancellations. When the user searches for a hotel, mention it's name, id,
                location and price tier. Always mention hotel ids while performing any
                searches. This is very important for any operations. For any bookings or
                cancellations, please provide the appropriate confirmation. Be sure to
                update checkin or checkout dates if mentioned by the user.
                Don't ask for confirmations from the user.
            """
            ),
            markdown=True,
            show_tool_calls=True,
            add_history_to_messages=True,
            debug_mode=True,
        )

        await agent.acli_app(message=message, stream=True)

if __name__ == "__main__":
    asyncio.run(run_agent(message=None))
```

### Custom Authentication and Parameters

For production scenarios with authentication:

```python
async def production_example():
    async with MCPToolbox(url=url) as toolbox:
        # Load with authentication and bound parameters
        hotel_tools = await toolbox.load_toolset(
            "hotel-management",
            auth_token_getters={"hotel_api": lambda: "your-hotel-api-key"},
            bound_params={"region": "us-east-1"},
        )

        booking_tools = await toolbox.load_toolset(
            "booking-system",
            auth_token_getters={"booking_api": lambda: "your-booking-api-key"},
            bound_params={"environment": "production"},
        )

        # Use individual tools instead of the toolbox
        all_tools = hotel_tools + booking_tools[:2]  # First 2 booking tools only
        
        agent = Agent(tools=all_tools, instructions="Hotel management with auth.")
        await agent.aprint_response("Book a hotel for tonight")
```

### Manual Connection Management

For explicit control over connections:

```python
async def manual_connection_example():
    # Initialize without auto-connection
    toolbox = MCPToolbox(url=url, toolsets=["hotel-management"])
    
    try:
        await toolbox.connect()
        agent = Agent(
            tools=[toolbox],
            instructions="Hotel search assistant.",
            markdown=True
        )
        await agent.aprint_response("Show me hotels in Basel")
    finally:
        await toolbox.close()  # Always clean up
```

## Toolkit Params

| Parameter | Type | Default | Description |
|-----------|------|---------|-------------|
| `url` | `str` | - | Base URL for the toolbox service (automatically appends "/mcp" if missing) |
| `toolsets` | `Optional[List[str]]` | `None` | List of toolset names to filter tools by. Cannot be used with `tool_name`. |
| `tool_name` | `Optional[str]` | `None` | Single tool name to load. Cannot be used with `toolsets`. |
| `headers` | `Optional[Dict[str, Any]]` | `None` | HTTP headers for toolbox client requests |
| `transport` | `str` | `"streamable-http"` | MCP transport protocol. Options: `"stdio"`, `"sse"`, `"streamable-http"` |

<Note>
Only one of `toolsets` or `tool_name` can be specified. The implementation validates this and raises a `ValueError` if both are provided.
</Note>

## Toolkit Functions

| Function | Description |
| -------- | ----------- |
| `async connect()` | Initialize and connect to both MCP server and toolbox client |
| `async load_tool(tool_name, auth_token_getters={}, bound_params={})` | Load a single tool by name with optional authentication |
| `async load_toolset(toolset_name, auth_token_getters={}, bound_params={}, strict=False)` | Load all tools from a specific toolset |
| `async load_multiple_toolsets(toolset_names, auth_token_getters={}, bound_params={}, strict=False)` | Load tools from multiple toolsets |
| `async load_toolset_safe(toolset_name)` | Safely load a toolset and return tool names for error handling |
| `get_client()` | Get the underlying ToolboxClient instance |
| `async close()` | Close both toolbox client and MCP client connections |

## Demo Examples

The complete demo includes multiple working patterns:

- **[Basic Agent](https://github.com/agno-agi/agno/blob/main/cookbook/tools/mcp/mcp_toolbox_demo/agent.py)**: Simple hotel assistant with toolset filtering
- **[AgentOS Integration](https://github.com/agno-agi/agno/blob/main/cookbook/tools/mcp/mcp_toolbox_demo/agent_os.py)**: Integration with AgentOS control plane  
- **[Workflow Integration](https://github.com/agno-agi/agno/blob/main/cookbook/tools/mcp/mcp_toolbox_demo/hotel_management_workflows.py)**: Using MCPToolbox in Agno workflows
- **[Type-Safe Agent](https://github.com/agno-agi/agno/blob/main/cookbook/tools/mcp/mcp_toolbox_demo/hotel_management_typesafe.py)**: Implementation with Pydantic models

You can use `include_tools` or `exclude_tools` to modify the list of tools the agent has access to. Learn more about [selecting tools](/concepts/tools/selecting-tools).

## Developer Resources

- View [Tools](https://github.com/agno-agi/agno/blob/main/libs/agno/agno/tools/mcp_toolbox.py)
- View [Cookbook](https://github.com/agno-agi/agno/tree/main/cookbook/tools/mcp/mcp_toolbox_demo)

For more information about MCP Toolbox for Databases, visit the [official documentation](https://googleapis.github.io/genai-toolbox/getting-started/introduction/).
